Benjamin Reavill

Staff Agentic AI Engineer / AI Engineer $200,000 - $250,000 San Francisco, CA Onsite, 5x per week in office Full time / Permanent Most "agentic AI" roles are still research projects dressed up as products.This one isn't. The agent is live, in production, handling real workflows for Tesla, BMW, Meta, and Amazon. You’ll be in the codebase from day one, improving an agent that's already shipping, not starting from a blank page.This company builds AI-powered automation for mechanical engineers. Think Claude Code, but for CAD, CAE, and PLM workflows. $32M raised, backed by Eric Schmidt and early investors in Anthropic and OpenAI. Over 1,000 customers running production workflows on the platform.They're hiring a Staff Engineer to own the agent intelligence layer, the system that takes an engineer's intent and executes it reliably across complex desktop software. What you'd own:Evals infrastructure and agent benchmarking - defining what "good" looks like for a domain with no established benchmarkAgent harness build-out and ongoing performance improvement (task success rate, token efficiency, workflow coverage)Architecture decisions: tool-calling strategy, state management, context handling, model routing, error recoveryTechnical leadership of a small team of AI engineers - player-coach, not pure manager The profile they're looking for:Proven expertise building agentic systems into production. Systems that take real actions - tool-calling, multi-step state, failure handling, cost constraints. Ideally 2 yearsStrong on evals: task completion, failure mode analysis, regression detectionProduction-first mindset - you'd rather ship 70% coverage reliably than demo a clever system you can't measureBuilders over researchers. Too much academic background is a flag here Desktop automation experience is nice-to-have. Mechanical engineering background is nice-to-have. Experience taking agentic systems into production is the bar.

Machine Learning Engineer – Speech Model Training $250,000 - $300,000 San Francisco, CA Hybrid, 3x per week in office Full time / Permanent In this role you won’t be wrapping APIs or fine-tuning existing models. You’ll be building models across raw acoustic signal processing all the way through to production inference on edge devices. At a company that actually ships to 1.5M live users. A profitable, fast-growing AI company ($250M ARR in under three years, no VC dependency) is standing up a SpeechLLM lab from scratch. This is a founding seat on that team. They build a hardware-software AI companion used daily by over 1.5 million professionals worldwide. The next chapter is a world-class speech intelligence core and they need the engineers to architect it. What you'd own:Design and train large-scale speech models end-to-end. Unified SpeechLLMs, ASR, expressive TTS, generative audioOwn the full stack from acoustic feature engineering to GPU cluster optimisationRun and optimise distributed training at scale via PyTorch or JAX, FSDP, DeepSpeed, etcDrive real-time inference performance with vLLM, TensorRT-LLM, or SGLangApply RL alignment techniques to improve conversational qualityDebug the hard problems in distributed infrastructure and ship solutions You likely have:Proven experience training large-scale audio or speech models from the ground upDeep PyTorch or JAX expertise with real distributed training experienceGenuine comfort traversing the entire ML stack from signal processing to productionA bias toward shipping: you take ownership, you iterate fastStrong bonus: neural audio codecs, diffusion/flow-matching architectures, or LLM pretraining experience. Why joinProfitable company at ~$250M run rate - you'll see the impact of your work immediately in a product used daily by professionals worldwideDirect ownership of the live speech quality stack, not a supporting role in a large orgHybrid San Francisco team with real access to large, diverse, multilingual audio datasetsShort feedback loops - improvements ship fast and metrics are visibleClear path toward senior technical leadership as the audio team grows

Machine Learning Engineer - Live Agent & Speech Post-Processing$200,000 - $300,000San Francisco, hybrid (3x per week) Full time / PermanentThis company builds AI tools and devices that help professionals capture and use what's said in real conversations across meetings, calls, voice notes. It's profitable, bootstrapped, and scaling fast: $250M revenue run rate in under three years, used by over 1.5 million people globally.The product works. Now they need someone to make the live speech experience feel polished and seamless, fixing the small things that frustrate users at scale.What you'll doBuild and maintain test suites and automated evaluation platforms for multilingual, multi-model live systems. Covering hallucinations, casing, punctuation, number formatting, and segmentationSet up benchmarks for live agent systems: VAD false triggers, interruption latency, and turn-taking transitionsFix the friction points that hurt user experience: poor segmentation, inconsistent casing, hallucinated words Optimize VAD, barge-in models, and turn-taking logic to reduce end-to-end latency and false interruption ratesWhat "great" looks like1–3 years of hands-on experience in speech algorithm training, with a focus on pre- or post-processing, or full-duplex voice system optimizationYou've worked on ASR pre-processing or post-processing in a real productYou understand how live voice systems break and know how to fix themYou have published research at Interspeech or ICASSP, or possess speech-related patentsWhy joinProfitable company at ~$250M run rate - you'll see the impact of your work immediately in a product used daily by professionals worldwideDirect ownership of the live speech quality stack, not a supporting role in a large orgHybrid San Francisco team with real access to large, diverse, multilingual audio datasetsShort feedback loops - improvements ship fast and metrics are visibleClear path toward senior technical leadership as the audio team grows

Machine Learning Engineer - On-Device Speech Recognition$200,000 - $300,000San Francisco, hybrid (3x per week)Full time / PermanentThis company builds AI-powered tools that help professionals capture and use what's said in the real world of work - meetings, conversations, voice notes. It's profitable, bootstrapped, and growing fast: $250M revenue run rate in under three years, with over 1.5 million users globally.The product is working. The next step is making the speech engine significantly better by making it smaller, faster, and more accurate across every device and language it runs on.What you'll doDesign and train lightweight on-device ASR models (e.g. Streaming Transducer, CTC) that run efficiently on mobile and embedded hardwareCompress and optimize models using quantization, pruning, and knowledge distillationClean, align, and augment multilingual speech data; handle low-resource languages and noisy real-world conditionsWork closely with engineering teams to convert and deploy models into productionWhat "great" looks likeYou've trained or fine-tuned ASR models at production scale, not just in research settingsYou know at least one major ASR framework deeply (Wenet, Espnet, Icefall/K2, or Zipformer) and understand how they actually work at a structural levelYou've deployed on-device or offline ASR models and solved the messy problems that come with real hardware constraintsYou've done hands-on post-training quantization and know how to recover accuracy when it degradesMaster's or PhD in Computer Science, Signal Processing, or similar, and 3–5 years in speech algorithmsBonus: published research at ICASSP or Interspeech, experience with Zipformer / Paraformer / SenseVoice, or knowledge distillation from large speech models to compact ones.Why joinProfitable, fast-moving company. Your work ships and gets used by over a million peopleReal ownership of the on-device speech stack, not one task on a large team's backlogHybrid San Francisco team building both hardware and AI systems in parallelMeaningful datasets and global product scale to test and prove your workClear growth toward senior technical leadership as the audio function expands

Senior Technical Program Manager – Applied AI$180,000 – $200,000 Fully Remote (US East Coast preferred) Full-Time / PermanentA fast-growing AI language technology company is looking for a Senior Technical Program Manager to join their Applied AI team. They work with some of the world's largest organisations (including major government agencies and global enterprises) helping them translate and localise content at scale using cutting-edge AI. This is a hands-on programme management role. You will be overseeing the delivery of large datasets and custom engineering projects that are used directly to train and improve frontier AI models.Why JoinSmall, cross-functional teams where senior hires have real ownership over programmes end-to-endBacked by top-tier investors, this is a well-funded company with strong commercial tractionCompetitive base, equity, and benefitsWork that sits at the frontier of AI development, your programmes directly influence the next generation of large language modelsThe RoleYou will lead the delivery of complex technical programmes for major AI research partners. In practice, this means managing the pipelines that produce large volumes of high-quality training data - across text, audio, video, and image - and making sure that data reaches research teams accurately and on time.You will also oversee bespoke engineering workstreams, things like: retrieval-augmented generation (RAG) improvements, model evaluation projects, and synthetic data generation. You are the main point of contact for the AI researchers and engineers you work with, and you will translate their research needs into clear delivery plans.This is not a scrum master role. You need to understand what engineers are building and why, well enough to spot problems, ask the right questions, and earn the trust of technical teams on both sides.What We're Looking ForExperience managing large-scale data delivery programmes, ideally for AI or machine learning teamsA technical background. You don't need to write production code daily, but you should be comfortable reading it, reviewing it, and discussing it with engineersHands-on knowledge of modern AI concepts: training data pipelines, model evaluation, retrieval systems (RAG), and human feedback loops (RLHF)Experience working with multiple data types - not just text, but also audio, video, or image datasetsStrong stakeholder management skills at a senior levelAbility to operate in a fast-moving environment where priorities can shift with the latest research developmentsUseful but not essential:Proficiency in PythonFamiliarity with vector databases or agentic AI workflowsExperience working directly with AI research labs or frontier model teamsMultilingual backgroundWhat Success Looks LikeProgrammes delivered on time with clean, well-validated dataResearch partners feel well-supported and clearly communicated withEngineering workstreams run efficiently with minimal bottlenecksYou spot quality issues before they reach the modelTech / Domain ContextData pipelines · Multimodal datasets · RAG architectures · RLHF/RLAIF · Vector databases · Cloud infrastructure · RESTful APIs · Model evaluation

Senior Data Engineer - HealthTech$150,000 - $200,000  Hybrid - Houston, TX Full time / Permanent A fast-growing healthcare technology start up is looking for a Senior Data Engineer to join their team. They are actively working with large healthcare organizations across the U.S, helping them get more value from their data through AI-powered clinical tools. This work has a direct impact on how care is delivered — and the data teams sit at the centre of that. This is a hands-on role. You will be building and owning data pipelines that feed real AI systems used by clinicians every day. Why JoinSmall, collaborative teams where senior engineers have real ownershipClear progression to director. The company is growing and promotes from withinCompetitive base salary, equity, flexible hours, and strong benefitsWork that has a tangible impact on patient care across the U.S.The Role You will join a small team responsible for integrating data from large healthcare organisations into a modern cloud data platform. Day to day, you will be building pipelines, validating data quality, and making sure the right data reaches the right systems reliably and on time. You will also contribute to shared tools and frameworks that make future integrations faster, work that scales well beyond your individual projects. What We're Looking For4 years of experience building production data pipelinesStrong SQL skills across large, complex datasetsProficiency in Python for data transformationExperience with cloud-based data platforms and distributed processing toolsComfortable working with healthcare data formats and standards, or willing to learn quicklyExperience with Azure cloud servicesUseful but not essential:Background in healthcare data or EHR systemsExperience with modern lakehouse architecturesExposure to real-time data pipelines or message-based data feedsExperience in a SaaS or multi-tenant environmentTech Stack Azure Data Factory - Databricks - Python - SQL - PySpark - CI/CD tooling - Healthcare data standards What Success Looks LikePipelines delivered on time, well tested, and clearly documentedData quality issues caught early — before they reach productionReusable components that speed up future workStrong working relationships with partner technical teamsNoteworthy - This is a full-time / permanent role and cannot be considered for C2C, C2H, or any other temporary contracts.

Speech Algorithm Engineer (Speech LLM / SpeechLLM)$200,000 - $300,000San Francisco, Hybrid 3x per week in officeFull time / PermanentAbout the Role This company is already profitable, growing fast, and used by over 1.5M professionals globally. Revenue is tracking at ~$250M in under three years. The product works and is highly marketable, the next step is making its speech system significantly more accurate across languages, industries, and real-world conversations. We’re hiring a speech algorithm engineer to improve speaker diarization and keyword recognition in productio. This is applied, high-impact work that ships. What You’ll DoImprove speaker diarization and multi-language speech recognition accuracy in real customer conversationsDesign and optimize hotword and terminology recognition systems for industry-specific use casesFine-tune and train large speech models on substantial audio datasetsBuild clear evaluation frameworks to measure keyword accuracy and speaker separation performanceCompare open-source and commercial ASR systems and push performance beyond themWork closely with product and engineering to deploy models into live systems used dailyWhat “Great” Looks LikeYou’ve trained or fine-tuned speech models on large-scale datasets (not small research-only projects)You understand how speech systems behave in noisy, real-world conditionsYou’ve improved measurable production metrics (accuracy, diarization quality, keyword recall)You can read research and turn it into working systemsYou take ownership when performance drops Notable: If your experience is limited to light experimentation or purely academic research without production exposure, this likely won’t be a fit. Why JoinProfitable company at ~$250M run rateHybrid San Francisco team building both hardware and AI systemsReal ownership and visibility, not one engineer in a large orgGlobal product scale and meaningful datasetsClear growth path toward senior technical leadership as the audio function expandsStrong data security and compliance standards, this is enterprise-grade infrastructure